This article discusses performance analysis of a part of speech tagging task.

This presentation accompanies a paper discussing research on a novel scheme to reduce static leakage energy in SRAM arrays.

This paper discusses automatic generating of back-of-the-book indexes.

This paper discusses Natural Language Processing (NLP).

This paper investigates the problem of automatic humor recognition, and provides an in-depth analysis of two of the most frequently observed features of humorous text: human-centeredness and negative polarity. Through experiments performed on two collections of humorous texts, the authors show that these properties of verbal humor are consisted across different data sets.

This presentation discusses Robocamp, a special summer camp that was created by the University of North Texas (UNT) Computer Science and Engineering department. Robocamp successfully promotes engineering among high school women.

This paper describes the efforts and results of a plan for actively recruiting students to undergraduate computer science and engineering programs at the University of North Texas (UNT). Such recruitment of students is critical to the country's efforts to increase the number of engineering professionals, and is a priority for the Computer Science and Engineering (CSE) Department at UNT.

In this article, an enhanced channel-assignment algorithm at the Access Points (APs) of a Wireless Local Area Network (WLAN) is validated.

This article discusses text and structural data mining of influenza mentions in web and social media.

Paper accompanying a poster presentation for the 2013 International iConference. This paper discusses teaching tools, applications, and infrastructure for digital curation through the use of a virtual lab.

Poster presented at the 2013 International iConference. This poster discusses teaching tools, applications, and infrastructure for digital curation through the use of a virtual lab.

Paper from the Web-Scale Classification: Classifying Big Data from the Web Workshop. This paper proposes novel features that result in effective and efficient classification models for automatic identification of research articles.

Article proposes a performance metric and evaluates an existing adaptation process that dynamically adjusts to optimal network performance determined by Fractional Frequency Reuse (FFR) mechanism with mobile users.

Interview with Dr. Ryan Garlick for the Osher Lifelong Learning Institute (OLLI) podcast. In this episode, Susan speaks with Dr. Ryan Garlick, Principal Lecturer in UNT's Department of Computer Science and Engineering. They discuss his codebreaking work, including his participation in TV programs such as National Geographic's "Hunt for the Zodiac Killer." Dr. Garlick gives an overview of the codebreaking methods that are being used to decipher the Zodiac's mysterious messages and also talks about his academic and professional background.

Article proposes a Social- and Content-aware Video content delivery Prediction method (SCVP) to address the problem of predicting whether a video will be watched by a user for efficient video content delivery in mobile social networks.

This article aims to explore new categorization that characterizes the distribution clusters of visceral and subcutaneous adipose tissues (VAT and SAT) measured by magnetic resonance imaging (MRI), to analyze the relationship between the VAT-SAT distribution patterns and the novel body shape descriptors (BSDs), and to develop a classifier to predict the fat distribution clusters using the BSDs.

This article studies the problem of comparing the similarity and dissimilarity between two distinct vehicular trajectories by proposing an adjacency-based metric. This approach has a broad application in building truthfulness by comparing the similarity between two vehicles and evaluating the dissimilarity between two distinct paths in hazardous materials transportation.

Article is a study analyzing the global perceptions and perspectives towards COVID-19 vaccination using a worldwide Twitter dataset, natural language processing, and machine learning.

Article discusses how visual object tracking aims to continuously localize the target object of interest in a video sequence. To provide the community an overview, in this commentary, the authors discuss visual tracking from different aspects.

Data management plan for the grant, "Collaborative Research: IRES Track I: Wireless Federated Fog Computing for Remote Industry 4.0 Applications."